Quality Money Management
Process Engineering and Best Practices for Systematic Trading and InvestmentBy
- Andrew Kumiega
- Benjamin Van Vliet
The financial markets industry is at the same crossroads as the automotive industry in the late 1970s. Margins are collapsing and customization is rapidly increasing. The automotive industry turned to quality and its no coincidence that in the money management industry many of the spectacular failures have been due largely to problems in quality control. The financial industry in on the verge of a quality revolution. New and old firms alike are creating new investment vehicles and new strategies that are radically changing the nature of the industry. To compete, mutual funds, hedge fund industries, banks and proprietary trading firms are being forced to quicklyy research, test and implement trade selection and execution systems. And, just as in the early stages of factory automation, quality suffers and leads to defects. Many financial firms fall short of quality, lacking processes and methodologies for proper development and evaluation of trading and investment systems. Authors Kumiega and Van Vliet present a new step-by-step methodology for such development. Their methodology (called K|V) has been presented in numerous journal articles and at academic and industry conferences and is rapidly being accepted as the preferred business process for the institutional trading and hedge fund industries for development, presentation, and evaluation of trading and investment systems. The K|V model for trading system development combines new product development, project management and software development methodologies into one robust system. After four stages, the methodology requires repeating the entire waterfall for continuous improvement. The discussion quality and its applications to the front office is presented using lessons learned by the authors after using the methodology in the real world. As a result, it is flexible and modifiable to fit various projects in finance in different types of firms. Their methodology works equally well for short-term trading systems, longer-term portfolio management or mutual fund style investment strategies as well as more sophisticated ones employing derivative instruments in hedge funds.Additionally, readers will be able to quickly modify the standard K|V methodology to meet their unique needs and to quickly build other quantitatively drive applications for finance. At the beginning and the end of the book the authors pose a key question: Are you willing to change and embrace quality for the 21st century or are willing to accept extinction?The real gem in this book is that the concepts give the reader a road map to avoid extinction.
Primary audience: CIOs and IT Directors in financial services industry, particularly investment houses and banks; software vendors and technology companies who provide solutions for financial services industry; graduate students in financial engineering and financial markets courses and programs.
Hardbound, 304 Pages
Published: February 2008
Imprint: Academic Press
âBenjamin Van Vliet and Andrew Kumiega give a complete and methodological approach to building trading and investment systems. They cover all you need to know to understand back-testing and prototyping of trading algorithms. Our team had their methodology in mind when they designed our analytical tool, Resolver One, to ensure quality, reliability and consistency when developing trading systems from ideas through prototype to production. A one-stop book for building systematic trading and investment systems.â--Jean Viry-Babel, Head of Sales, ResolverSystems, London, United Kingdom "I believe Kumiega and Van Vliet's blending of two disciplines - Quality and Finance - is the next step in the evolution of the financial industry. This approach will make financial processes more effective and efficient."--M. Zia Hassan, Fellow of the American Society for Quality, Dean Emeritus and Professor, Stuart School of Business, Chicago IL "Andrew Kumiega, a manager in charge of software testing at a Chicago-based trading firm and co- author of âQuality Money Management,â a book that discusses the importance of standards for financial technology, says he is not surprised by the software glitch suffered by Knight because automated trading is still a young industry. It has yet to establish industry-wide standards and frequently suffers from the cross-purposes of three competing groups: traders who view their primary goal as trading success while upholding securities regulations, programmers who focus on coding and creating well designed software, and quantitative analysts who hone in on the mathematics that underpin many trading software efforts. âIf you look at these three groups, the tactics they employ for effective software testing are all completely different,â Kumiega said."--Institutional Investor
- ContentsPrefaceCHAPTER 1 IntroductionCHAPTER 2 Key Concepts and Definitions of TermsCHAPTER 3 Overview of the Trading/Investment System Development MethodologyCHAPTER 4 Managing Design and DevelopmentCHAPTER 5 Types of Trading SystemsCHAPTER 6 Stage 0: The Money DocumentSTAGE 1: Design and Document Trading/Investment StrategyCHAPTER 7 STAGE 1: OverviewCHAPTER 8 Describe Trading/Investment IdeaCHAPTER 9 Research Quantitative MethodsCHAPTER 10 Prototype in Modeling SoftwareCHAPTER 11 Check PerformanceCHAPTER 12 Gate 1STAGE 2: BacktestCHAPTER 13 STAGE 2: OverviewCHAPTER 14 Gather Historical DataCHAPTER 15 Develop Cleaning AlgorithmsCHAPTER 16 Perform In â Sample / Out â of â Sample TestsCHAPTER 17 Check Performance and Shadow Trade CHAPTER 18 Gate 2STAGE 3: ImplementCHAPTER 19 STAGE 3: OverviewCHAPTER 20 Plan and Document Technology SpecificationsCHAPTER 21 Design System ArchitectureCHAPTER 22 Build and Document the SystemCHAPTER 23 Check Performance and Probationary TradeCHAPTER 24 Gate 3STAGE 4: Manage Portfolio and RiskCHAPTER 25 STAGE 4: OverviewCHAPTER 26 Plan Performance and Risk ProcessesCHAPTER 27 Define Performance ControlsCAHPTER 28 Perform SPC AnalysisCHAPTER 29 Determine Causes of VariationCHAPTER 30 Kaizen: Continuous Improvement